Improving the evaluation of worldwide biomedical research output
As part of our research on new applications of big data in healthcare, we’ve developed a method for mapping biomedical research at the disease level. As a result, policymakers and administrators can more accurately evaluate historical research output and make better-informed decisions when allocating research funding and creating research portfolios. This method makes it possible to systematically examine which institutions are publishing research on which diseases, and to compare disease-level research output such as publication volume and quality worldwide. These insights can also be linked to other available disease-specific details, such as disease burden and healthcare costs.
In collaboration with the Centre for Science and Technology Studies (CWTS) at Leiden University, we developed a method for classifying biomedical research by disease and rating its impact. That might seem obvious, but was not yet available, because authors often use different names for the same condition. Large databases of biomedical publications, like Web of Science or Scopus, are only divided by discipline, such as ‘oncology’ or ‘neurology’. Furthermore, there was no good way to compare quality and publication volume between different diseases. To enable a fair comparison, we developed a method that takes major differences in size and citations between research areas into account. To do so, we made use of text mining techniques.
With this study, we hope to contribute to making portfolio management more objective for countries and institutions. We’re curious to hear your reactions, and look forward to discussing our results with interested parties.